The use of genomic testing for selecting replacement heifers in commercial farms has recently attracted much attention. Fertility traits are among the most complex, hard to measure, and lowly heritable traits, and hence they can benefit the most from genomic testing. The objectives of this study were to assess the relationship between early genomic prediction of daughter pregnancy rate (GDPR) and pregnancy at the first service (P1), pregnancy at the end of lactation (PEND), number of services for conception (NSFC), days from calving to first service (TP1), and days open (TPEND). Data for GDPR, milk production, and reproductive outcomes from 1,401 multiparous and 3,044 primiparous Holstein cows from 4 commercial farms with the same reproductive management were used in the analyses. All animals were genotyped and genomically evaluated as heifers before first breeding, so no phenotypic data were available for predicting genomic merits. In addition, all animals were genotyped and evaluated as heifers before first breeding, so no phenotypic data were available for prediction. Data for GDPR and milk production were categorized in quartiles. The statistical models included GDPR, farm-year-season of the first insemination, milk yield, breeding code (estrus detection or timed artificial insemination), and the interaction terms as potential predictors for the different reproductive outcomes evaluated. Data were analyzed separately for primiparous and multiparous cows. The proportion of cows bred by estrus detection increased linearly from lowest to highest GDPR in primiparous cows. There were positive associations of GDPR for P1, PEND, NSFC, TP1, and TPEND in both primiparous and multiparous cows. For instance, positive GDPR effects in multiparous cows included a 15.7% higher P1 (47.6% vs. 31.9%), 11.9% higher PEND (84.9% vs. 73.0%), and 48.0-d shorter TPEND (139.8 vs. 175.7 d) for the highest quartile compared with the lowest quartile. Milk yield affected PEND in multiparous cows, and TPEND and NSFC affected PEND in primiparous cows. The only significant interaction between GDPR and milk production was detected for NSFC in primiparous cows, where high-producing cows showed a reduction in NSFC as GDPR increased, whereas low-producing cows showed no relationship between GDPR and NSFC. Overall, our findings show that GDPR can be effectively used as a predictor of future reproductive performance, reaffirming the potential benefits of applying early genomic predictions for making accurate early selection decisions.